fractal organizations part i – complexity
TRANSCRIPT
FRACTAL ORGANIZATIONS
Part I - COMPLEXITY
FATMA CcedilINAR Mba
KUTLU MERİH Phd
Systems as Complex Beings
Complex Systems characteristics
Complex Adaptation of Systems CAS
Organizations as Complex Adaptive Systems
Edge of Chaos
Self Orgnization amp Emergence
Part I Fundamental Concepts of Complexity Theory
Presentation Outline
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The Reasons of Object Oriented Approach
Description of the Objects
Organization as a Complex of Objects
Object Oriented Business Modelling
Organizational Agents
Sycamore Tree Diagram of Organizations
Organizational Sycamore Tree Agents
The CORTEX
(CBBC) ndash Complexity Business Balance Cardrdquo
Presentation Outline
Part II Object Based Complexity Approach
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
In this study with two parts we propose a new modelling technique based on Object BasedComplexity Modelling of the of the organizations
First we describe the basic aspects of Complexity approach Part I
Then we redefine the concept of complexity Andapplication to organizations by the aid of laquoobject orientationraquo concept of software technology Part II
Then we apply this new approach to set up a new management paradigm as Sycamore Tree Diagramand Complexity
IntroductionO
bje
ct-
Ba
sed
Co
mp
lex
ity
Mo
deli
ng
Ap
pli
ca
tio
n
Te
ch
niq
ues
Why Complexity Based Approach
For contemporary organizations
analytical and quantitative modeling
techniques are not sufficient for
modeling of the complex structured
corporate management activities
Mathematical and statistical methods
lack of performance to express the
impact of intangible factors
That makes mandatory to use new
models that are based on organic
thinking Informatics and control theory
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Fundamental Problems of Contemporary
Organizations
All technical and business practices applied in
contemporary organizations fails to simplify the
complexity of situation
They also far from to cover structural relations
which are necessary for a good model
TQM is a delicate Japanese flower
which has no chance to live on rocky
American mountains
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Fundamental Problems of Contemporary
OrganizationsDead Diagrams of the Analytical World
Designing stylish organigrams come before to define
the problems correctly and fail to represent the
relations and analyse them correctly
Representing the multi-dimension organizations on
the paper with two dimension do more harm than its
benefits
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Why Fractal Nesting
Relations and time are the intangible assets of
the business to be managed
They have a metric on their own which we can
not measure but we know that they affect
business performance
This metric can be changed in the process but
we are unable to express it as mathematical
and arithmetical concepts
For This Reason We Apply the Fractal Concept
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Nowadays we are able to pick up
business processes within few days with
the internet and logistics support
That means that the performance metrics
has changed at the same time also
increased the level of performance
Why Fractal Nesting
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The Reasons of the Object Oriented Approach
Conventional analytical models was not able to reflect
the dynamics of the process of functional data but only
the status at a given moment
With the Object -based modeling model always is in
communication with the available mass of data and the
many interventions can be made on-line real-time
The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments
Object -Based Models
are direct
management tools
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Until recently the light by which science was working was
only able to illuminate simple linear systems
The advent of the computer and big data warehouses
changed things
It is now possible to look at systems as complex beings
which has strange behaviour patterns
Fundamental Concepts of Complexıty Theory
Systems as Complex Beings
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The field is still very new and there is no agreement about terms and
terminology but the following quotes enough to give us a flavour
Complex adaptive systems consist of a number of components or agents that
interact with each other according to sets of rules that require them to examine
and respond to each otherrsquos behaviour in order to improve their behaviour and
thus the behaviour of the system they comprise (Stacey 1996)
A system that is complex in the sense that a great many independent agents
are interacting with each other in a great many ways (Waldrop 1993)
What is a complex system
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity Arises Interacting of Simple Components
In a complex system you generally find that the basic components and the basic laws are
quite simple the complexity arises because you have a great many of these simple
components interacting simultaneously
The complex whole may exhibit properties that are not readily explained by understanding its
parts
Because complexity results from the interaction between the components of a system
complexity is manifested at the level of the system itself
To understand the behavior of a complex system we must understand not only the behaviour
of the parts but how they act together to form the whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Small set of simple rules
Some approaches have been used to model behaviours in the natural world
One of the pioneers was Craig Reynolds (1987) who modelled flocking
behaviour using a small set of rules
Separation steer to avoid crowding local flockmates
Alignment steer towards the average heading of local flockmates
Cohesion steer to move toward the average position of local flockmates
These three simple rules can change a random assembly of agents into a
cohesive group looking just like a flock of birds or shoal of fish
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Systems as Complex Beings
Complex Systems characteristics
Complex Adaptation of Systems CAS
Organizations as Complex Adaptive Systems
Edge of Chaos
Self Orgnization amp Emergence
Part I Fundamental Concepts of Complexity Theory
Presentation Outline
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The Reasons of Object Oriented Approach
Description of the Objects
Organization as a Complex of Objects
Object Oriented Business Modelling
Organizational Agents
Sycamore Tree Diagram of Organizations
Organizational Sycamore Tree Agents
The CORTEX
(CBBC) ndash Complexity Business Balance Cardrdquo
Presentation Outline
Part II Object Based Complexity Approach
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
In this study with two parts we propose a new modelling technique based on Object BasedComplexity Modelling of the of the organizations
First we describe the basic aspects of Complexity approach Part I
Then we redefine the concept of complexity Andapplication to organizations by the aid of laquoobject orientationraquo concept of software technology Part II
Then we apply this new approach to set up a new management paradigm as Sycamore Tree Diagramand Complexity
IntroductionO
bje
ct-
Ba
sed
Co
mp
lex
ity
Mo
deli
ng
Ap
pli
ca
tio
n
Te
ch
niq
ues
Why Complexity Based Approach
For contemporary organizations
analytical and quantitative modeling
techniques are not sufficient for
modeling of the complex structured
corporate management activities
Mathematical and statistical methods
lack of performance to express the
impact of intangible factors
That makes mandatory to use new
models that are based on organic
thinking Informatics and control theory
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Fundamental Problems of Contemporary
Organizations
All technical and business practices applied in
contemporary organizations fails to simplify the
complexity of situation
They also far from to cover structural relations
which are necessary for a good model
TQM is a delicate Japanese flower
which has no chance to live on rocky
American mountains
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Fundamental Problems of Contemporary
OrganizationsDead Diagrams of the Analytical World
Designing stylish organigrams come before to define
the problems correctly and fail to represent the
relations and analyse them correctly
Representing the multi-dimension organizations on
the paper with two dimension do more harm than its
benefits
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Why Fractal Nesting
Relations and time are the intangible assets of
the business to be managed
They have a metric on their own which we can
not measure but we know that they affect
business performance
This metric can be changed in the process but
we are unable to express it as mathematical
and arithmetical concepts
For This Reason We Apply the Fractal Concept
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Nowadays we are able to pick up
business processes within few days with
the internet and logistics support
That means that the performance metrics
has changed at the same time also
increased the level of performance
Why Fractal Nesting
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The Reasons of the Object Oriented Approach
Conventional analytical models was not able to reflect
the dynamics of the process of functional data but only
the status at a given moment
With the Object -based modeling model always is in
communication with the available mass of data and the
many interventions can be made on-line real-time
The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments
Object -Based Models
are direct
management tools
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Until recently the light by which science was working was
only able to illuminate simple linear systems
The advent of the computer and big data warehouses
changed things
It is now possible to look at systems as complex beings
which has strange behaviour patterns
Fundamental Concepts of Complexıty Theory
Systems as Complex Beings
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The field is still very new and there is no agreement about terms and
terminology but the following quotes enough to give us a flavour
Complex adaptive systems consist of a number of components or agents that
interact with each other according to sets of rules that require them to examine
and respond to each otherrsquos behaviour in order to improve their behaviour and
thus the behaviour of the system they comprise (Stacey 1996)
A system that is complex in the sense that a great many independent agents
are interacting with each other in a great many ways (Waldrop 1993)
What is a complex system
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity Arises Interacting of Simple Components
In a complex system you generally find that the basic components and the basic laws are
quite simple the complexity arises because you have a great many of these simple
components interacting simultaneously
The complex whole may exhibit properties that are not readily explained by understanding its
parts
Because complexity results from the interaction between the components of a system
complexity is manifested at the level of the system itself
To understand the behavior of a complex system we must understand not only the behaviour
of the parts but how they act together to form the whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Small set of simple rules
Some approaches have been used to model behaviours in the natural world
One of the pioneers was Craig Reynolds (1987) who modelled flocking
behaviour using a small set of rules
Separation steer to avoid crowding local flockmates
Alignment steer towards the average heading of local flockmates
Cohesion steer to move toward the average position of local flockmates
These three simple rules can change a random assembly of agents into a
cohesive group looking just like a flock of birds or shoal of fish
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The Reasons of Object Oriented Approach
Description of the Objects
Organization as a Complex of Objects
Object Oriented Business Modelling
Organizational Agents
Sycamore Tree Diagram of Organizations
Organizational Sycamore Tree Agents
The CORTEX
(CBBC) ndash Complexity Business Balance Cardrdquo
Presentation Outline
Part II Object Based Complexity Approach
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
In this study with two parts we propose a new modelling technique based on Object BasedComplexity Modelling of the of the organizations
First we describe the basic aspects of Complexity approach Part I
Then we redefine the concept of complexity Andapplication to organizations by the aid of laquoobject orientationraquo concept of software technology Part II
Then we apply this new approach to set up a new management paradigm as Sycamore Tree Diagramand Complexity
IntroductionO
bje
ct-
Ba
sed
Co
mp
lex
ity
Mo
deli
ng
Ap
pli
ca
tio
n
Te
ch
niq
ues
Why Complexity Based Approach
For contemporary organizations
analytical and quantitative modeling
techniques are not sufficient for
modeling of the complex structured
corporate management activities
Mathematical and statistical methods
lack of performance to express the
impact of intangible factors
That makes mandatory to use new
models that are based on organic
thinking Informatics and control theory
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Fundamental Problems of Contemporary
Organizations
All technical and business practices applied in
contemporary organizations fails to simplify the
complexity of situation
They also far from to cover structural relations
which are necessary for a good model
TQM is a delicate Japanese flower
which has no chance to live on rocky
American mountains
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Fundamental Problems of Contemporary
OrganizationsDead Diagrams of the Analytical World
Designing stylish organigrams come before to define
the problems correctly and fail to represent the
relations and analyse them correctly
Representing the multi-dimension organizations on
the paper with two dimension do more harm than its
benefits
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Why Fractal Nesting
Relations and time are the intangible assets of
the business to be managed
They have a metric on their own which we can
not measure but we know that they affect
business performance
This metric can be changed in the process but
we are unable to express it as mathematical
and arithmetical concepts
For This Reason We Apply the Fractal Concept
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Nowadays we are able to pick up
business processes within few days with
the internet and logistics support
That means that the performance metrics
has changed at the same time also
increased the level of performance
Why Fractal Nesting
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The Reasons of the Object Oriented Approach
Conventional analytical models was not able to reflect
the dynamics of the process of functional data but only
the status at a given moment
With the Object -based modeling model always is in
communication with the available mass of data and the
many interventions can be made on-line real-time
The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments
Object -Based Models
are direct
management tools
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Until recently the light by which science was working was
only able to illuminate simple linear systems
The advent of the computer and big data warehouses
changed things
It is now possible to look at systems as complex beings
which has strange behaviour patterns
Fundamental Concepts of Complexıty Theory
Systems as Complex Beings
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The field is still very new and there is no agreement about terms and
terminology but the following quotes enough to give us a flavour
Complex adaptive systems consist of a number of components or agents that
interact with each other according to sets of rules that require them to examine
and respond to each otherrsquos behaviour in order to improve their behaviour and
thus the behaviour of the system they comprise (Stacey 1996)
A system that is complex in the sense that a great many independent agents
are interacting with each other in a great many ways (Waldrop 1993)
What is a complex system
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity Arises Interacting of Simple Components
In a complex system you generally find that the basic components and the basic laws are
quite simple the complexity arises because you have a great many of these simple
components interacting simultaneously
The complex whole may exhibit properties that are not readily explained by understanding its
parts
Because complexity results from the interaction between the components of a system
complexity is manifested at the level of the system itself
To understand the behavior of a complex system we must understand not only the behaviour
of the parts but how they act together to form the whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Small set of simple rules
Some approaches have been used to model behaviours in the natural world
One of the pioneers was Craig Reynolds (1987) who modelled flocking
behaviour using a small set of rules
Separation steer to avoid crowding local flockmates
Alignment steer towards the average heading of local flockmates
Cohesion steer to move toward the average position of local flockmates
These three simple rules can change a random assembly of agents into a
cohesive group looking just like a flock of birds or shoal of fish
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
In this study with two parts we propose a new modelling technique based on Object BasedComplexity Modelling of the of the organizations
First we describe the basic aspects of Complexity approach Part I
Then we redefine the concept of complexity Andapplication to organizations by the aid of laquoobject orientationraquo concept of software technology Part II
Then we apply this new approach to set up a new management paradigm as Sycamore Tree Diagramand Complexity
IntroductionO
bje
ct-
Ba
sed
Co
mp
lex
ity
Mo
deli
ng
Ap
pli
ca
tio
n
Te
ch
niq
ues
Why Complexity Based Approach
For contemporary organizations
analytical and quantitative modeling
techniques are not sufficient for
modeling of the complex structured
corporate management activities
Mathematical and statistical methods
lack of performance to express the
impact of intangible factors
That makes mandatory to use new
models that are based on organic
thinking Informatics and control theory
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Fundamental Problems of Contemporary
Organizations
All technical and business practices applied in
contemporary organizations fails to simplify the
complexity of situation
They also far from to cover structural relations
which are necessary for a good model
TQM is a delicate Japanese flower
which has no chance to live on rocky
American mountains
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Fundamental Problems of Contemporary
OrganizationsDead Diagrams of the Analytical World
Designing stylish organigrams come before to define
the problems correctly and fail to represent the
relations and analyse them correctly
Representing the multi-dimension organizations on
the paper with two dimension do more harm than its
benefits
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Why Fractal Nesting
Relations and time are the intangible assets of
the business to be managed
They have a metric on their own which we can
not measure but we know that they affect
business performance
This metric can be changed in the process but
we are unable to express it as mathematical
and arithmetical concepts
For This Reason We Apply the Fractal Concept
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Nowadays we are able to pick up
business processes within few days with
the internet and logistics support
That means that the performance metrics
has changed at the same time also
increased the level of performance
Why Fractal Nesting
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The Reasons of the Object Oriented Approach
Conventional analytical models was not able to reflect
the dynamics of the process of functional data but only
the status at a given moment
With the Object -based modeling model always is in
communication with the available mass of data and the
many interventions can be made on-line real-time
The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments
Object -Based Models
are direct
management tools
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Until recently the light by which science was working was
only able to illuminate simple linear systems
The advent of the computer and big data warehouses
changed things
It is now possible to look at systems as complex beings
which has strange behaviour patterns
Fundamental Concepts of Complexıty Theory
Systems as Complex Beings
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The field is still very new and there is no agreement about terms and
terminology but the following quotes enough to give us a flavour
Complex adaptive systems consist of a number of components or agents that
interact with each other according to sets of rules that require them to examine
and respond to each otherrsquos behaviour in order to improve their behaviour and
thus the behaviour of the system they comprise (Stacey 1996)
A system that is complex in the sense that a great many independent agents
are interacting with each other in a great many ways (Waldrop 1993)
What is a complex system
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity Arises Interacting of Simple Components
In a complex system you generally find that the basic components and the basic laws are
quite simple the complexity arises because you have a great many of these simple
components interacting simultaneously
The complex whole may exhibit properties that are not readily explained by understanding its
parts
Because complexity results from the interaction between the components of a system
complexity is manifested at the level of the system itself
To understand the behavior of a complex system we must understand not only the behaviour
of the parts but how they act together to form the whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Small set of simple rules
Some approaches have been used to model behaviours in the natural world
One of the pioneers was Craig Reynolds (1987) who modelled flocking
behaviour using a small set of rules
Separation steer to avoid crowding local flockmates
Alignment steer towards the average heading of local flockmates
Cohesion steer to move toward the average position of local flockmates
These three simple rules can change a random assembly of agents into a
cohesive group looking just like a flock of birds or shoal of fish
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Why Complexity Based Approach
For contemporary organizations
analytical and quantitative modeling
techniques are not sufficient for
modeling of the complex structured
corporate management activities
Mathematical and statistical methods
lack of performance to express the
impact of intangible factors
That makes mandatory to use new
models that are based on organic
thinking Informatics and control theory
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Fundamental Problems of Contemporary
Organizations
All technical and business practices applied in
contemporary organizations fails to simplify the
complexity of situation
They also far from to cover structural relations
which are necessary for a good model
TQM is a delicate Japanese flower
which has no chance to live on rocky
American mountains
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Fundamental Problems of Contemporary
OrganizationsDead Diagrams of the Analytical World
Designing stylish organigrams come before to define
the problems correctly and fail to represent the
relations and analyse them correctly
Representing the multi-dimension organizations on
the paper with two dimension do more harm than its
benefits
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Why Fractal Nesting
Relations and time are the intangible assets of
the business to be managed
They have a metric on their own which we can
not measure but we know that they affect
business performance
This metric can be changed in the process but
we are unable to express it as mathematical
and arithmetical concepts
For This Reason We Apply the Fractal Concept
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Nowadays we are able to pick up
business processes within few days with
the internet and logistics support
That means that the performance metrics
has changed at the same time also
increased the level of performance
Why Fractal Nesting
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The Reasons of the Object Oriented Approach
Conventional analytical models was not able to reflect
the dynamics of the process of functional data but only
the status at a given moment
With the Object -based modeling model always is in
communication with the available mass of data and the
many interventions can be made on-line real-time
The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments
Object -Based Models
are direct
management tools
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Until recently the light by which science was working was
only able to illuminate simple linear systems
The advent of the computer and big data warehouses
changed things
It is now possible to look at systems as complex beings
which has strange behaviour patterns
Fundamental Concepts of Complexıty Theory
Systems as Complex Beings
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The field is still very new and there is no agreement about terms and
terminology but the following quotes enough to give us a flavour
Complex adaptive systems consist of a number of components or agents that
interact with each other according to sets of rules that require them to examine
and respond to each otherrsquos behaviour in order to improve their behaviour and
thus the behaviour of the system they comprise (Stacey 1996)
A system that is complex in the sense that a great many independent agents
are interacting with each other in a great many ways (Waldrop 1993)
What is a complex system
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity Arises Interacting of Simple Components
In a complex system you generally find that the basic components and the basic laws are
quite simple the complexity arises because you have a great many of these simple
components interacting simultaneously
The complex whole may exhibit properties that are not readily explained by understanding its
parts
Because complexity results from the interaction between the components of a system
complexity is manifested at the level of the system itself
To understand the behavior of a complex system we must understand not only the behaviour
of the parts but how they act together to form the whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Small set of simple rules
Some approaches have been used to model behaviours in the natural world
One of the pioneers was Craig Reynolds (1987) who modelled flocking
behaviour using a small set of rules
Separation steer to avoid crowding local flockmates
Alignment steer towards the average heading of local flockmates
Cohesion steer to move toward the average position of local flockmates
These three simple rules can change a random assembly of agents into a
cohesive group looking just like a flock of birds or shoal of fish
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Fundamental Problems of Contemporary
Organizations
All technical and business practices applied in
contemporary organizations fails to simplify the
complexity of situation
They also far from to cover structural relations
which are necessary for a good model
TQM is a delicate Japanese flower
which has no chance to live on rocky
American mountains
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Fundamental Problems of Contemporary
OrganizationsDead Diagrams of the Analytical World
Designing stylish organigrams come before to define
the problems correctly and fail to represent the
relations and analyse them correctly
Representing the multi-dimension organizations on
the paper with two dimension do more harm than its
benefits
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Why Fractal Nesting
Relations and time are the intangible assets of
the business to be managed
They have a metric on their own which we can
not measure but we know that they affect
business performance
This metric can be changed in the process but
we are unable to express it as mathematical
and arithmetical concepts
For This Reason We Apply the Fractal Concept
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Nowadays we are able to pick up
business processes within few days with
the internet and logistics support
That means that the performance metrics
has changed at the same time also
increased the level of performance
Why Fractal Nesting
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The Reasons of the Object Oriented Approach
Conventional analytical models was not able to reflect
the dynamics of the process of functional data but only
the status at a given moment
With the Object -based modeling model always is in
communication with the available mass of data and the
many interventions can be made on-line real-time
The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments
Object -Based Models
are direct
management tools
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Until recently the light by which science was working was
only able to illuminate simple linear systems
The advent of the computer and big data warehouses
changed things
It is now possible to look at systems as complex beings
which has strange behaviour patterns
Fundamental Concepts of Complexıty Theory
Systems as Complex Beings
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The field is still very new and there is no agreement about terms and
terminology but the following quotes enough to give us a flavour
Complex adaptive systems consist of a number of components or agents that
interact with each other according to sets of rules that require them to examine
and respond to each otherrsquos behaviour in order to improve their behaviour and
thus the behaviour of the system they comprise (Stacey 1996)
A system that is complex in the sense that a great many independent agents
are interacting with each other in a great many ways (Waldrop 1993)
What is a complex system
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity Arises Interacting of Simple Components
In a complex system you generally find that the basic components and the basic laws are
quite simple the complexity arises because you have a great many of these simple
components interacting simultaneously
The complex whole may exhibit properties that are not readily explained by understanding its
parts
Because complexity results from the interaction between the components of a system
complexity is manifested at the level of the system itself
To understand the behavior of a complex system we must understand not only the behaviour
of the parts but how they act together to form the whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Small set of simple rules
Some approaches have been used to model behaviours in the natural world
One of the pioneers was Craig Reynolds (1987) who modelled flocking
behaviour using a small set of rules
Separation steer to avoid crowding local flockmates
Alignment steer towards the average heading of local flockmates
Cohesion steer to move toward the average position of local flockmates
These three simple rules can change a random assembly of agents into a
cohesive group looking just like a flock of birds or shoal of fish
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Fundamental Problems of Contemporary
OrganizationsDead Diagrams of the Analytical World
Designing stylish organigrams come before to define
the problems correctly and fail to represent the
relations and analyse them correctly
Representing the multi-dimension organizations on
the paper with two dimension do more harm than its
benefits
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Why Fractal Nesting
Relations and time are the intangible assets of
the business to be managed
They have a metric on their own which we can
not measure but we know that they affect
business performance
This metric can be changed in the process but
we are unable to express it as mathematical
and arithmetical concepts
For This Reason We Apply the Fractal Concept
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Nowadays we are able to pick up
business processes within few days with
the internet and logistics support
That means that the performance metrics
has changed at the same time also
increased the level of performance
Why Fractal Nesting
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The Reasons of the Object Oriented Approach
Conventional analytical models was not able to reflect
the dynamics of the process of functional data but only
the status at a given moment
With the Object -based modeling model always is in
communication with the available mass of data and the
many interventions can be made on-line real-time
The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments
Object -Based Models
are direct
management tools
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Until recently the light by which science was working was
only able to illuminate simple linear systems
The advent of the computer and big data warehouses
changed things
It is now possible to look at systems as complex beings
which has strange behaviour patterns
Fundamental Concepts of Complexıty Theory
Systems as Complex Beings
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The field is still very new and there is no agreement about terms and
terminology but the following quotes enough to give us a flavour
Complex adaptive systems consist of a number of components or agents that
interact with each other according to sets of rules that require them to examine
and respond to each otherrsquos behaviour in order to improve their behaviour and
thus the behaviour of the system they comprise (Stacey 1996)
A system that is complex in the sense that a great many independent agents
are interacting with each other in a great many ways (Waldrop 1993)
What is a complex system
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity Arises Interacting of Simple Components
In a complex system you generally find that the basic components and the basic laws are
quite simple the complexity arises because you have a great many of these simple
components interacting simultaneously
The complex whole may exhibit properties that are not readily explained by understanding its
parts
Because complexity results from the interaction between the components of a system
complexity is manifested at the level of the system itself
To understand the behavior of a complex system we must understand not only the behaviour
of the parts but how they act together to form the whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Small set of simple rules
Some approaches have been used to model behaviours in the natural world
One of the pioneers was Craig Reynolds (1987) who modelled flocking
behaviour using a small set of rules
Separation steer to avoid crowding local flockmates
Alignment steer towards the average heading of local flockmates
Cohesion steer to move toward the average position of local flockmates
These three simple rules can change a random assembly of agents into a
cohesive group looking just like a flock of birds or shoal of fish
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Why Fractal Nesting
Relations and time are the intangible assets of
the business to be managed
They have a metric on their own which we can
not measure but we know that they affect
business performance
This metric can be changed in the process but
we are unable to express it as mathematical
and arithmetical concepts
For This Reason We Apply the Fractal Concept
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Nowadays we are able to pick up
business processes within few days with
the internet and logistics support
That means that the performance metrics
has changed at the same time also
increased the level of performance
Why Fractal Nesting
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The Reasons of the Object Oriented Approach
Conventional analytical models was not able to reflect
the dynamics of the process of functional data but only
the status at a given moment
With the Object -based modeling model always is in
communication with the available mass of data and the
many interventions can be made on-line real-time
The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments
Object -Based Models
are direct
management tools
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Until recently the light by which science was working was
only able to illuminate simple linear systems
The advent of the computer and big data warehouses
changed things
It is now possible to look at systems as complex beings
which has strange behaviour patterns
Fundamental Concepts of Complexıty Theory
Systems as Complex Beings
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The field is still very new and there is no agreement about terms and
terminology but the following quotes enough to give us a flavour
Complex adaptive systems consist of a number of components or agents that
interact with each other according to sets of rules that require them to examine
and respond to each otherrsquos behaviour in order to improve their behaviour and
thus the behaviour of the system they comprise (Stacey 1996)
A system that is complex in the sense that a great many independent agents
are interacting with each other in a great many ways (Waldrop 1993)
What is a complex system
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity Arises Interacting of Simple Components
In a complex system you generally find that the basic components and the basic laws are
quite simple the complexity arises because you have a great many of these simple
components interacting simultaneously
The complex whole may exhibit properties that are not readily explained by understanding its
parts
Because complexity results from the interaction between the components of a system
complexity is manifested at the level of the system itself
To understand the behavior of a complex system we must understand not only the behaviour
of the parts but how they act together to form the whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Small set of simple rules
Some approaches have been used to model behaviours in the natural world
One of the pioneers was Craig Reynolds (1987) who modelled flocking
behaviour using a small set of rules
Separation steer to avoid crowding local flockmates
Alignment steer towards the average heading of local flockmates
Cohesion steer to move toward the average position of local flockmates
These three simple rules can change a random assembly of agents into a
cohesive group looking just like a flock of birds or shoal of fish
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Nowadays we are able to pick up
business processes within few days with
the internet and logistics support
That means that the performance metrics
has changed at the same time also
increased the level of performance
Why Fractal Nesting
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The Reasons of the Object Oriented Approach
Conventional analytical models was not able to reflect
the dynamics of the process of functional data but only
the status at a given moment
With the Object -based modeling model always is in
communication with the available mass of data and the
many interventions can be made on-line real-time
The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments
Object -Based Models
are direct
management tools
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Until recently the light by which science was working was
only able to illuminate simple linear systems
The advent of the computer and big data warehouses
changed things
It is now possible to look at systems as complex beings
which has strange behaviour patterns
Fundamental Concepts of Complexıty Theory
Systems as Complex Beings
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The field is still very new and there is no agreement about terms and
terminology but the following quotes enough to give us a flavour
Complex adaptive systems consist of a number of components or agents that
interact with each other according to sets of rules that require them to examine
and respond to each otherrsquos behaviour in order to improve their behaviour and
thus the behaviour of the system they comprise (Stacey 1996)
A system that is complex in the sense that a great many independent agents
are interacting with each other in a great many ways (Waldrop 1993)
What is a complex system
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity Arises Interacting of Simple Components
In a complex system you generally find that the basic components and the basic laws are
quite simple the complexity arises because you have a great many of these simple
components interacting simultaneously
The complex whole may exhibit properties that are not readily explained by understanding its
parts
Because complexity results from the interaction between the components of a system
complexity is manifested at the level of the system itself
To understand the behavior of a complex system we must understand not only the behaviour
of the parts but how they act together to form the whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Small set of simple rules
Some approaches have been used to model behaviours in the natural world
One of the pioneers was Craig Reynolds (1987) who modelled flocking
behaviour using a small set of rules
Separation steer to avoid crowding local flockmates
Alignment steer towards the average heading of local flockmates
Cohesion steer to move toward the average position of local flockmates
These three simple rules can change a random assembly of agents into a
cohesive group looking just like a flock of birds or shoal of fish
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The Reasons of the Object Oriented Approach
Conventional analytical models was not able to reflect
the dynamics of the process of functional data but only
the status at a given moment
With the Object -based modeling model always is in
communication with the available mass of data and the
many interventions can be made on-line real-time
The capability to reach the data and functions on-line real-time provides the models the ability to more effectively monitor and intervene in real-world developments
Object -Based Models
are direct
management tools
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Until recently the light by which science was working was
only able to illuminate simple linear systems
The advent of the computer and big data warehouses
changed things
It is now possible to look at systems as complex beings
which has strange behaviour patterns
Fundamental Concepts of Complexıty Theory
Systems as Complex Beings
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The field is still very new and there is no agreement about terms and
terminology but the following quotes enough to give us a flavour
Complex adaptive systems consist of a number of components or agents that
interact with each other according to sets of rules that require them to examine
and respond to each otherrsquos behaviour in order to improve their behaviour and
thus the behaviour of the system they comprise (Stacey 1996)
A system that is complex in the sense that a great many independent agents
are interacting with each other in a great many ways (Waldrop 1993)
What is a complex system
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity Arises Interacting of Simple Components
In a complex system you generally find that the basic components and the basic laws are
quite simple the complexity arises because you have a great many of these simple
components interacting simultaneously
The complex whole may exhibit properties that are not readily explained by understanding its
parts
Because complexity results from the interaction between the components of a system
complexity is manifested at the level of the system itself
To understand the behavior of a complex system we must understand not only the behaviour
of the parts but how they act together to form the whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Small set of simple rules
Some approaches have been used to model behaviours in the natural world
One of the pioneers was Craig Reynolds (1987) who modelled flocking
behaviour using a small set of rules
Separation steer to avoid crowding local flockmates
Alignment steer towards the average heading of local flockmates
Cohesion steer to move toward the average position of local flockmates
These three simple rules can change a random assembly of agents into a
cohesive group looking just like a flock of birds or shoal of fish
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Until recently the light by which science was working was
only able to illuminate simple linear systems
The advent of the computer and big data warehouses
changed things
It is now possible to look at systems as complex beings
which has strange behaviour patterns
Fundamental Concepts of Complexıty Theory
Systems as Complex Beings
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The field is still very new and there is no agreement about terms and
terminology but the following quotes enough to give us a flavour
Complex adaptive systems consist of a number of components or agents that
interact with each other according to sets of rules that require them to examine
and respond to each otherrsquos behaviour in order to improve their behaviour and
thus the behaviour of the system they comprise (Stacey 1996)
A system that is complex in the sense that a great many independent agents
are interacting with each other in a great many ways (Waldrop 1993)
What is a complex system
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity Arises Interacting of Simple Components
In a complex system you generally find that the basic components and the basic laws are
quite simple the complexity arises because you have a great many of these simple
components interacting simultaneously
The complex whole may exhibit properties that are not readily explained by understanding its
parts
Because complexity results from the interaction between the components of a system
complexity is manifested at the level of the system itself
To understand the behavior of a complex system we must understand not only the behaviour
of the parts but how they act together to form the whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Small set of simple rules
Some approaches have been used to model behaviours in the natural world
One of the pioneers was Craig Reynolds (1987) who modelled flocking
behaviour using a small set of rules
Separation steer to avoid crowding local flockmates
Alignment steer towards the average heading of local flockmates
Cohesion steer to move toward the average position of local flockmates
These three simple rules can change a random assembly of agents into a
cohesive group looking just like a flock of birds or shoal of fish
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
The field is still very new and there is no agreement about terms and
terminology but the following quotes enough to give us a flavour
Complex adaptive systems consist of a number of components or agents that
interact with each other according to sets of rules that require them to examine
and respond to each otherrsquos behaviour in order to improve their behaviour and
thus the behaviour of the system they comprise (Stacey 1996)
A system that is complex in the sense that a great many independent agents
are interacting with each other in a great many ways (Waldrop 1993)
What is a complex system
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity Arises Interacting of Simple Components
In a complex system you generally find that the basic components and the basic laws are
quite simple the complexity arises because you have a great many of these simple
components interacting simultaneously
The complex whole may exhibit properties that are not readily explained by understanding its
parts
Because complexity results from the interaction between the components of a system
complexity is manifested at the level of the system itself
To understand the behavior of a complex system we must understand not only the behaviour
of the parts but how they act together to form the whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Small set of simple rules
Some approaches have been used to model behaviours in the natural world
One of the pioneers was Craig Reynolds (1987) who modelled flocking
behaviour using a small set of rules
Separation steer to avoid crowding local flockmates
Alignment steer towards the average heading of local flockmates
Cohesion steer to move toward the average position of local flockmates
These three simple rules can change a random assembly of agents into a
cohesive group looking just like a flock of birds or shoal of fish
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity Arises Interacting of Simple Components
In a complex system you generally find that the basic components and the basic laws are
quite simple the complexity arises because you have a great many of these simple
components interacting simultaneously
The complex whole may exhibit properties that are not readily explained by understanding its
parts
Because complexity results from the interaction between the components of a system
complexity is manifested at the level of the system itself
To understand the behavior of a complex system we must understand not only the behaviour
of the parts but how they act together to form the whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Small set of simple rules
Some approaches have been used to model behaviours in the natural world
One of the pioneers was Craig Reynolds (1987) who modelled flocking
behaviour using a small set of rules
Separation steer to avoid crowding local flockmates
Alignment steer towards the average heading of local flockmates
Cohesion steer to move toward the average position of local flockmates
These three simple rules can change a random assembly of agents into a
cohesive group looking just like a flock of birds or shoal of fish
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Small set of simple rules
Some approaches have been used to model behaviours in the natural world
One of the pioneers was Craig Reynolds (1987) who modelled flocking
behaviour using a small set of rules
Separation steer to avoid crowding local flockmates
Alignment steer towards the average heading of local flockmates
Cohesion steer to move toward the average position of local flockmates
These three simple rules can change a random assembly of agents into a
cohesive group looking just like a flock of birds or shoal of fish
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex System Characteristics
In the early days of complex systems theory the emphasis was on large
networks of simple agents with simple interactions
More recently there has been a realisation that smaller networks of complex
agents can show the same kinds of behaviour and can be equally complex
Complex systems have a number of properties some of which are listed
below
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Nested (Fractal) So an economy is made up of
organisations
which are made up departments
which are made up of people
which are made up of organs
Which are made up tissues
which are made up of cells
all of which are complex adaptive systems
The key aspect of complex adaptive systems is that the components of the systemmdashusually referred to as agentsmdashas themselves complex adaptive systems
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Are Open
Complex systems are open
systemsmdashthat is energy and
information are constantly being
imported and exported across
system boundaries
Complex systems interact with
other complex systems through
their boundaries
It is usually difficult to determine the
boundaries of a complex system
The decision is usually based on the
observerrsquos perceptive needs and
prejudices rather than any intrinsic
property of the system itself
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Has Dynamical Equilibrium
Dynamical open systems has a tendency
to maximize their entropy
Which causes to attain a dynamical
equilibrium
Because of this complex systems are
usually far from equilibrium
Even though there is constant change
there is also the appearance of stability
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There is a sense in which elements in a complex system cannot lsquoknowrsquo what is happening in the system as a whole
If they could all the complexity would have to be present in that element
Yet since the complexity is created by the relationships between elements that is simply impossible
A corollary of this is that no element in the system could hope to control the system
The Parts Cannot Contain The Whole
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Contain Nonlinear Feedback Loops
Both negative (damping) and positive
(amplifying) feedback are key ingredients of
complex systems
The effects of an agentrsquos actions are fed back to
the agent and this in turn affects the way the
agent behaves in the future
There are rarely simple cause and effect
relationships between elements
This set of constantly adapting nonlinear
relationships lies at the heart of what makes a
complex system special
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Relationships Are Short-Range
Typically the relationships between elements in a complex system are
short-range
information is normally received from near neighbours
The richness of the connections means that communications will pass
across the system but will probably be modified on the way
Contemporary information techniques overcome most of the
information barriers and deformations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complex Systems Have A History
The history of a complex system is important
and cannot be ignored
Even a small change in circumstances can
lead to large deviations in the future
That means TIME is a fundamental
component of a Complex System
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Emergence
What distinguishes a complex
system from a merely
complicated one is that some
behaviours and patterns emerge
in complex systems as a result
of the patterns of relationship
between the elements
Emergence is perhaps the key
property of complex systems
and a lot of work is being done
to try to understand more about
its nature and the conditions
which will help it to occur
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
There are many who would argue that
complexity is not just a metaphor for
organisations it is an adequate and
accurate description of organisations
It is to assert that an organisation is
more or less appropriately described in
terms of the insights being developed
by complexity theorists
However it must be recognised that
complexity theory is at present still very
tentative and undeveloped especially
in the field of human organisations
To speak of an organisation as a complex system is to adopt a theoretical stance
In that case we borrow the concept of ldquoObject Orientationrdquoconcepts from the software development technology tomerge Complexity andOrganization theories
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Are organisations complex adaptive systems
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Implications of Complexity Theory For Organisations
There are a number of implications which
complexity theory may potentially have
for organisations
We can only mention a few of them here
Inability to control
Inabilty to predict
Butterfly Effect
Edge of Chaos
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to control
Perhaps the most crucial but to clients the most controversial perspective from complexity theory is that it is impossible to controlwhat happens to the system
Mechanical metaphors still dominate most management thinking
So much management literature focuses on the role of the lsquoleaderthat they can lsquomake things happenrsquo
Yet a fundamental result of systems thinking in general and complexity theory in particular is that no one element can have enough complexity to be able to comprehend and control the system as a whole
If it can the system is not complex
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Inability to Predict
One of the features of complex systems is that they have
what is known as sensitivity to initial conditions
This means that a vanishingly small difference in the initial
conditions (whenever you choose to start) can make a
staggeringly large difference as time goes on
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Butterfly Effect
The classical formulation of this comes from meteorology
(Edward Lorenz a meteorologist was one of the first (1963)
to investigate the properties of complex systems such as
weather systems)
It states that even such a small perturbation as a butterfly
flapping its wings couldmdashbecause of the nonlinear nature of
the systemmdashlead to a tornado some months or years later
Of course the chances are that it wonrsquot the real issue is that
it is theoretically impossible to predict whether or not it will
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Threshold of Change For Organizations
This concept may help to deal with a key question in organisation development
ldquohow can we know if an organisation is ready to changerdquo
The answer is that we cannot know (though intuition may often be a reliable
guide) but there are some key variables which have a significant effect on
readiness and ability to change
If there is too much stability in the system change is unlikely
if there is too much randomness the system will not be able to form any
coherent patterns
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of chaos
Langton discovered that as he changed the value of a particular variable his simulation suddenly exhibited ordered behaviour and then became disordered again
The region where changes occurred he called the edge of chaos
A key concept in much writing about complexity and organisations is the edge of chaos
It has been popularised by Stuart Kauffman (1995) of the Santa Fe Institute the leading centre for the study of complex adaptive systems
The term was actually coined by Chris Langton another worker at Santa Fe who was working with a kind of computer simulation called a cellular automaton
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Connectivity Diversity and Information Flow
Kaufmann and other researchers (see eg Kauffman 1995 Holland
1995 Bak 1997) working with computer simulations suggest that there
are three variables which are significant in moving systems to the edge
of chaos
connectivity
diversity and
information flow
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Edge of Chaos Can Work If
Basically stable systems can move towards the edge of chaos
1 if their agents become better connected
2 if there is more diversity (either in the agents themselves or in the nature of the relationships between them) and
3 if the amount of information transferred is increased
Conversely an unstable system one with too much randomness needs to reduce some or all of these variables
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Management as Optimum Control
Similarly if there is too much control in the form of high power differentials
between different parts of the organisation creativity and readiness for change
are likely to be stifled
Contrariwise if the control mechanisms are too weak the system can dissolve
into chaotic or random behaviour
Than managament becomes a problem of ldquoOptimum Controlrdquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Organisation amp Emergence
Perhaps the most interesting aspect of complex systems is their
ability to self-organise for ordered patterns to emerge simply as a
result of the relationships and interactions of the constituent
agents without any external control or design
When a complex system is at the edge of chaos it is in a state
where change may occur easily and spontaneously
When an organisation is poised at the edge of chaos even a small
stimulus may cause major change to ripple through like some
kind of domino effect
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Ability To Influence By Attractors
Another way of looking at emergence is to think about the dynamics of a complex system
If all states were equally likely then emergence would not occur Instead it appears that a relatively few configurations are lsquoprivilegedrsquo in some way
These configurations are sometimes known as attractors
There is a lot of misunderstanding of this term but it can be useful in helping to make sense of complex behaviour
So we could say that a complex system will self-organise onto an attractor
It is not possible to dictate the nature of the attractor because a complex system is intrinsically unpredictable and uncontrollable
The questions is can we influence the nature of the attractor which the system lsquochoosesrsquo
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
Because the environment of a CAS is made up of
other CASs all competing for resources the dynamic
between them is constantly changing in a nonlinear
fashion
In fact both competition and co-operation are at work
simultaneously leading not just to evolution but to co-
evolution
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Habitat Effect Co-Evolution
This complex lsquochicken-egg-chickenrsquo form of co-
evolution is absolutely key for understanding
complex systems and organisational change
Companies are neither masters nor slaves of their
destinies
New competitive and collaborative strategies are
now being explored in response to these insights
(Moore 1996 Nalebuff amp Brandenburger 1996)
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
FitnessAnother way of looking at this wider environment is to
consider the notion of lsquofitnessrsquo
At any given time some organisations are more successful than others they are lsquofitterrsquo than others
The fitness of a system changes over time because of the constantly changing environment which is being remade from moment to moment as an emergent result of the interactions between the systems
This means that a configuration which has a fitness f1 at time t1 (relative to the other systems in the environment) is most unlikely to have the same fitness at time t2
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
To Move In A Landscape Alters The Landscape
Actually things are even more complicated because as a system moves across a fitness landscape it changes the nature of the landscape by virtue of its interactions with other systems
Co-evolution has two messages for us that we can never control our environment and also that we need never be passive spectators as the landscapes change
What we do both affects and is affected by others
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Patching
Because the only way to get to a distant
fitness peak will involve getting less fit before
getting better organisations are often
reluctant to undertake such a journey
Even those chief execs who intuitively know
what has to be done seldom have models
which will help them articulate and
communicate their vision
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Self-Optimization with Patching
Patching breaks a system into connected chunks which then try to self-optimise
So an organisation might be broken into work groups business units profit centres etc Each is then given the freedom and encouragement to do as well as it canmdashto improve its own fitness
The side effect of success for any given patch may be to cause neighbouring patches to be worse off (go down a valley) and this may lead to the organisation becoming worse off for a time
But if the process is allowed to continue it will lead to eventual improvement as the system climbs a new peak one that could not have been reached by a simple adaptive walk
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Number of Patches are not Determined
Kauffman also found that for any given system which
he modelled that there is an optimum number of
patches to help the system move to a new fitness
peak
Unfortunately there is currently no known way to
predict that number even for a simple computer
simulation let alone a human organisation
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Complexity theory is an immature field still
developing It offers great challenge to the
organisation theorist and some tantalising
possibilities and models for the organisational
practitioner
For some it is too flaky too counter to common
sense for others it is an inexhaustible source of
stimulus and excitement
There is much more but so far is enough to develop
an Object Based Complexity Theory of
Organizations
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
CO
NC
LU
SIO
N
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
ldquo21TH CENTURY WILL BE
COMPLEX SCIENCE
CENTURYrdquo
Stephen HAWKING
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
kutlumerihnet
kutmerihgmailcom
fatmacinarspkgovtr
httpwwwspkgovtr
httpwwwriskonomicom
fatma_cinar_ftm
fractalorg
Riskonometri
Riskonomi
CORTEXIEN
trlinkedincompubkutlu-merih9b92125a
trlinkedincominfatmacinar
Contact
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES Allen P M (2001) ldquoA Complex Systems Approach to Learning in Adaptive Networksrdquo International Journal of
Innovation Management Vol 5 No2 pp 149 ndash 180
Ashkenas R Ulrich D Jick T and Kerr S (1995) ldquoThe Boundaryless Organization Breaking the Chains of
Organizational Structurerdquo Jossey-Bass San Francisco
Bak P Tang C ve Wiesenfeld K (1988) ldquoSelf - Organized Criticalityrdquo Physical Review 38 364 - 374
Battram A (1999) ldquoKarmaşıklıkta Yol Almakrdquo Ccedilev Z Dicleli Tuumlrk Henkel Dergisi Yayınları İstanbul
Willis R (2001) ldquoPersonal Communicationrdquo London
Capra F (1996) ldquoThe Web of Liferdquo HarperCollins London
Dale M (1994) ldquoLearning Organizationsrdquo in Mabey C and Iles P eds Managing Learning Routledge in association
with the Open University
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London p 157 158 164
Merih K ve Ccedilınar F (2013) ldquoModelling of Corporate Performance In Multi-Dimensional Complex StructuredOrganizations ldquoCbbcrdquo Approachrdquo Submitted to the EconAnadolu 2013 Anadolu International Conference in Economics
III June 19-21 2013 Eskişehir httpwwweconanadoluorgenindexphparticles20133683
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Kauffman S A (1996) ldquoAt Home in the Universe The Search for the Laws of Self Organization and Complexityrdquo Penguin Books
London
Kauffman S A (1991) ldquoAntichaos and Adaptation Biological Evolution May Have Been Shaped by More Than Just Natural
Selectionrdquo Scientific American 265 78-84
Kuhn T S (1996) ldquoThe Structure of Scientific Revolutionsrdquo 3 Bas University of Chicago Press (Tuumlrkccedilesi iccedilin bkz Bilimsel Devrimlerin
Yapısı Alan Yayıncılık)
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoModelling of Corporate Performance In Multi-Dimensional Complex Structured
Organizations ldquoCBBCrdquo Managementrdquo Submitted to the ldquo2nd International Symposium on Chaos Complexity and Leadership (ICCLS)
December 17-19 at Middle East Technical University (METU) Ankara Turkey
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoFinansal Karar Suumlreccedillerinde Grafik-Datamining Analizirdquo TROUGBIDW SIG Nisan 2014
İstanbul httpwwwtrougorgp=684
Kuumlccediluumlkoumlzmen C C ve Ccedilınar F (2014) ldquoGoumlrsel Veri Analizinde Devrimrdquo Soumlyleşi Ekonomik Ccediloumlzuumlm Temmuz 2014 httpekonomik-
cozumcomtrgorsel-veri-analizinde-devrim-mihtml
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoBanking Sector Analysis of Izmir Province A Graphical Data Mining Approachrdquo Submitted to
the 34th National Conference for Operations Research and Industrial Engineering (YAEM 2014) Goumlruumlkle Campus of Uludağ University in
Bursa Turkey on 25-27 June 2014
Kuumlccediluumlkoumlzmen C C and Ccedilınar F (2014) ldquoNew Sectoral Incentive System and Credit Defaults Graphic-Data Mining Analysisrdquo Submitted
to the ICEF 2014 Conference Yıldız Technical University in İstanbul Turkey on 08-09 Sep 2014
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Law A (1998) ldquoOpen Mindsrdquo Orion Business Books London
Lewin R and Regine B (1999) ldquoThe Soul at Workrdquo Orion Business Books p 105 London
Morgan G (1993) ldquoImaginizationrdquo Sage Newbury Park California
McMaster M D (1996) ldquoThe Intelligence Advantage Organizing for Complexityrdquo Newton MA Butterworth Heinemann
Rakotobe-Joel T eds University of Warwick UK
Mabey C Salaman G Storey J (2001) ldquoOrganizational Structuring and Restructuringrdquo in Salaman G ed
Understanding Business Organisations Routledge London
McMillan E (2000) ldquoUsing Self Organising Principles to create effective projet teams as part of an organisational
change intervention A case study of the Open Universityrdquo in Complexity and Complex Systems in Industry McCarthy I
And Rakotobe-Joel T Eds University of Warwick UK
Mathew K M White M C ve Long R (1999) ldquoWhy Studying the Complexity Sciences in the Social Sciencesrdquo
Human Relations 52 439-462
Mumford E and Hendricks R (1996) ldquoBusiness Process Re-Engineering RIPrdquo Personnel Management Institute of
Personnel and Development May McCarthy I and Rakotobe-Joel T eds University of Warwick UK
Prigogine L Nicholis O ve Babloyantz A (1972 a) ldquoThermodynamics of Evolution Part Irdquo Physics Today 25 23-28 -
Prigogine L Nicholis O ve Babloyantz A (1972 b) ldquoThermodynamics of Evolution Part IIrdquo Physics Today 25 38-44
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY
Pedroni M and Bertrand Meyer (2009) ldquoObject-oriented modeling of Object-Oriented Conceptsrdquo lsquoA
Case Study in Structuring an Educational Domainrsquo Chair of Software Engineering ETH Zurich Switzerland
ltfmichelapedroni|bertrandmeyerginfethzchgt
Slocum R K and Frondorf D S (2000) ldquoBusiness Management Using a Fractally-Scaled Structurerdquo
Complexity and Complex Systems in Industry
Thomas C C and Coe T (1991) ldquoThe Flat Organisation Philosophy and Practicerdquo British Institute of
Management
Wheatley M (1994) ldquo Leadership and the New Sciencerdquo Berrett- Koehler San Francisco - Capra F
(1996) ldquoThe Web of Liferdquo HarperCollins London
Wheatley M (1994) ldquoLeadership and the New Sciencerdquo Berrett- Koehler San Francisco
Waldrop M M (1994) ldquoComplexityrdquo Penguin Books New York
Waldrop M M (1997) ldquoKarmaşıklık Duumlzen ve Kaosun Eşiğinde Beliren Bilimrdquo (Ccedilev Z Dicleli)
İstanbul Tuumlrk Henkel Dergisi Yayınları
RESOURCES
FRACTAL ORGANIZATIONS Part I - COMPLEXITY